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Update version to 0.9.0
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‎README.md

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Cortex is an open source platform that takes machine learning models—trained with nearly any framework—and turns them into production web APIs in one command. <br>
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<!-- Delete on release branches -->
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<!-- CORTEX_VERSION_README_MINOR x1 -->
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[install](https://www.cortex.dev/install) • [docs](https://www.cortex.dev) • [examples](https://github.com/cortexlabs/cortex/tree/0.8/examples) • [we're hiring](https://angel.co/cortex-labs-inc/jobs) • [email us](mailto:[email protected]) • [chat with us](https://gitter.im/cortexlabs/cortex)<br><br>
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<!-- Set header Cache-Control=no-cache on the S3 object metadata (see https://help.github.com/en/articles/about-anonymized-image-urls) -->
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![Demo](https://cortex-public.s3-us-west-2.amazonaws.com/demo/gif/v0.8.gif)<br>
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### Step 1: Configure your deployment
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<!-- CORTEX_VERSION_README_MINOR -->
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Define a `deployment` and an `api` resource. A `deployment` specifies a set of APIs that are deployed together. An `api` makes a model available as a web service that can serve real-time predictions. The configuration below will download the model from the `cortex-examples` S3 bucket. You can run the code that generated the model [here](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.8/examples/text-generator/gpt-2.ipynb).
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Define a `deployment` and an `api` resource. A `deployment` specifies a set of APIs that are deployed together. An `api` makes a model available as a web service that can serve real-time predictions. The configuration below will download the model from the `cortex-examples` S3 bucket. You can run the code that generated the model [here](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/text-generator/gpt-2.ipynb).
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```yaml
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# cortex.yaml
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## More examples
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<!-- CORTEX_VERSION_README_MINOR x3 -->
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- [Iris classification](https://github.com/cortexlabs/cortex/tree/0.8/examples/iris-classifier)
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- [Iris classification](https://github.com/cortexlabs/cortex/tree/0.9/examples/iris-classifier)
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- [Sentiment analysis](https://github.com/cortexlabs/cortex/tree/0.8/examples/sentiment-analysis) with BERT
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- [Sentiment analysis](https://github.com/cortexlabs/cortex/tree/0.9/examples/sentiment-analysis) with BERT
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- [Image classification](https://github.com/cortexlabs/cortex/tree/0.8/examples/image-classifier) with Inception v3 and AlexNet
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- [Image classification](https://github.com/cortexlabs/cortex/tree/0.9/examples/image-classifier) with Inception v3 and AlexNet
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<br>
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‎build/build-image.sh

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ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")"/.. >/dev/null && pwd)"
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CORTEX_VERSION=master
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CORTEX_VERSION=0.9.0
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dir=$1
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image=$2

‎build/cli.sh

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ROOT="$(cd "$(dirname "${BASH_SOURCE[0]}")"/.. >/dev/null && pwd)"
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CORTEX_VERSION=master
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CORTEX_VERSION=0.9.0
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arg1=${1:-""}
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upload="false"

‎build/push-image.sh

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set -euo pipefail
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CORTEX_VERSION=master
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CORTEX_VERSION=0.9.0
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image=$1
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‎cortex.sh

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### CONFIGURATION ###
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#####################
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export CORTEX_VERSION_BRANCH_STABLE=master
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export CORTEX_VERSION_BRANCH_STABLE=0.9.0
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export CORTEX_CONFIG="${CORTEX_CONFIG:-""}"
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if [ "$CORTEX_CONFIG" != "" ]; then

‎docs/cluster/config.md

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export CORTEX_NODES_MAX=5
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# Image paths
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export CORTEX_IMAGE_MANAGER="cortexlabs/manager:master"
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export CORTEX_IMAGE_FLUENTD="cortexlabs/fluentd:master"
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export CORTEX_IMAGE_STATSD="cortexlabs/statsd:master"
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export CORTEX_IMAGE_OPERATOR="cortexlabs/operator:master"
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export CORTEX_IMAGE_TF_SERVE="cortexlabs/tf-serve:master"
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export CORTEX_IMAGE_TF_API="cortexlabs/tf-api:master"
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export CORTEX_IMAGE_TF_SERVE_GPU="cortexlabs/tf-serve-gpu:master"
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export CORTEX_IMAGE_ONNX_SERVE="cortexlabs/onnx-serve:master"
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export CORTEX_IMAGE_ONNX_SERVE_GPU="cortexlabs/onnx-serve-gpu:master"
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export CORTEX_IMAGE_CLUSTER_AUTOSCALER="cortexlabs/cluster-autoscaler:master"
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export CORTEX_IMAGE_NVIDIA="cortexlabs/nvidia:master"
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export CORTEX_IMAGE_METRICS_SERVER="cortexlabs/metrics-server:master"
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export CORTEX_IMAGE_ISTIO_PROXY="cortexlabs/istio-proxy:master"
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export CORTEX_IMAGE_ISTIO_PILOT="cortexlabs/istio-pilot:master"
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export CORTEX_IMAGE_ISTIO_CITADEL="cortexlabs/istio-citadel:master"
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export CORTEX_IMAGE_ISTIO_GALLEY="cortexlabs/istio-galley:master"
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export CORTEX_IMAGE_DOWNLOADER="cortexlabs/downloader:master"
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export CORTEX_IMAGE_MANAGER="cortexlabs/manager:0.9.0"
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export CORTEX_IMAGE_FLUENTD="cortexlabs/fluentd:0.9.0"
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export CORTEX_IMAGE_STATSD="cortexlabs/statsd:0.9.0"
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export CORTEX_IMAGE_OPERATOR="cortexlabs/operator:0.9.0"
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export CORTEX_IMAGE_TF_SERVE="cortexlabs/tf-serve:0.9.0"
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export CORTEX_IMAGE_TF_API="cortexlabs/tf-api:0.9.0"
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export CORTEX_IMAGE_TF_SERVE_GPU="cortexlabs/tf-serve-gpu:0.9.0"
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export CORTEX_IMAGE_ONNX_SERVE="cortexlabs/onnx-serve:0.9.0"
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export CORTEX_IMAGE_ONNX_SERVE_GPU="cortexlabs/onnx-serve-gpu:0.9.0"
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export CORTEX_IMAGE_CLUSTER_AUTOSCALER="cortexlabs/cluster-autoscaler:0.9.0"
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export CORTEX_IMAGE_NVIDIA="cortexlabs/nvidia:0.9.0"
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export CORTEX_IMAGE_METRICS_SERVER="cortexlabs/metrics-server:0.9.0"
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export CORTEX_IMAGE_ISTIO_PROXY="cortexlabs/istio-proxy:0.9.0"
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export CORTEX_IMAGE_ISTIO_PILOT="cortexlabs/istio-pilot:0.9.0"
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export CORTEX_IMAGE_ISTIO_CITADEL="cortexlabs/istio-citadel:0.9.0"
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export CORTEX_IMAGE_ISTIO_GALLEY="cortexlabs/istio-galley:0.9.0"
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export CORTEX_IMAGE_DOWNLOADER="cortexlabs/downloader:0.9.0"
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# Flag to enable collecting error reports and usage stats. If flag is not set to either "true" or "false", you will be prompted.
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export CORTEX_ENABLE_TELEMETRY=""

‎docs/cluster/install.md

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```bash
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# Download
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curl -O https://raw.githubusercontent.com/cortexlabs/cortex/master/cortex.sh
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curl -O https://raw.githubusercontent.com/cortexlabs/cortex/0.9/cortex.sh
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```bash
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# Clone the Cortex repository
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git clone -b 0.9 https://github.com/cortexlabs/cortex.git
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‎docs/cluster/python-client.md

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<!-- CORTEX_VERSION_BRANCH_STABLE, e.g. v0.9.0 -->
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```bash
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pip install git+https://github.com/cortexlabs/cortex.git@master#egg=cortex\&subdirectory=pkg/workloads/cortex/client
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pip install git+https://github.com/cortexlabs/cortex.git@v0.9.0#egg=cortex\&subdirectory=pkg/workloads/cortex/client
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The Python client needs to be initialized with AWS credentials and an operator URL for your Cortex cluster. You can find the operator URL by running `./cortex.sh endpoints`.

‎docs/cluster/uninstall.md

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```bash
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curl -O https://raw.githubusercontent.com/cortexlabs/cortex/0.9/cortex.sh
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‎docs/cluster/update.md

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‎docs/deployments/packaging-models.md

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## TensorFlow
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<!-- CORTEX_VERSION_MINOR -->
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Export your trained model and upload the export directory, or checkpoint directory containing the export directory, which is usually the case if you used `estimator.train_and_evaluate`. An example is shown below (here is the [complete example](https://github.com/cortexlabs/cortex/blob/master/examples/sentiment-analysis)):
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Export your trained model and upload the export directory, or checkpoint directory containing the export directory, which is usually the case if you used `estimator.train_and_evaluate`. An example is shown below (here is the [complete example](https://github.com/cortexlabs/cortex/blob/0.9/examples/sentiment-analysis)):
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```Python
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* [PyTorch](https://github.com/cortexlabs/cortex/blob/master/examples/iris-classifier/models/pytorch_model.py)
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* [Sklearn](https://github.com/cortexlabs/cortex/blob/master/examples/iris-classifier/models/sklearn_model.py)
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* [XGBoost](https://github.com/cortexlabs/cortex/blob/master/examples/iris-classifier/models/xgboost_model.py)
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* [Keras](https://github.com/cortexlabs/cortex/blob/master/examples/iris-classifier/models/keras_model.py)
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* [PyTorch](https://github.com/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/pytorch_model.py)
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* [Sklearn](https://github.com/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/sklearn_model.py)
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* [XGBoost](https://github.com/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/xgboost_model.py)
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* [Keras](https://github.com/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/keras_model.py)
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‎docs/summary.md

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* [Deploy machine learning models in production](../README.md)
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* [Install](cluster/install.md)
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* [GitHub](https://github.com/cortexlabs/cortex)
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* [Examples](https://github.com/cortexlabs/cortex/tree/master/examples) <!-- CORTEX_VERSION_MINOR -->
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* [Examples](https://github.com/cortexlabs/cortex/tree/0.9/examples) <!-- CORTEX_VERSION_MINOR -->
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* [We're hiring](https://angel.co/cortex-labs-inc/jobs)
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* [Email us](mailto:[email protected])
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* [Chat with us](https://gitter.im/cortexlabs/cortex)

‎examples/image-classifier/README.md

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You can run the code that generated the exported models used in this example folder here:
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- [Pytorch Alexnet](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/image-classifier/alexnet.ipynb)
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- [TensorFlow Inception V3](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/image-classifier/inception.ipynb)
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‎examples/image-classifier/alexnet.ipynb

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"That's it! See the [example on GitHub](https://github.com/cortexlabs/cortex/tree/master/examples/image-classifier) for how to deploy the model as an API."
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"That's it! See the [example on GitHub](https://github.com/cortexlabs/cortex/tree/0.9/examples/image-classifier) for how to deploy the model as an API."
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‎examples/image-classifier/inception.ipynb

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"That's it! See the [example on GitHub](https://github.com/cortexlabs/cortex/tree/0.9/examples/image-classifier) for how to deploy the model as an API."
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‎examples/iris-classifier/README.md

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- [Keras](https://colab.research.google.com/github/cortexlabs/cortex/blob/master/examples/iris-classifier/models/keras.ipynb)
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- [XGBoost](https://colab.research.google.com/github/cortexlabs/cortex/blob/master/examples/iris-classifier/models/xgboost.ipynb)
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- [sklearn](https://colab.research.google.com/github/cortexlabs/cortex/blob/master/examples/iris-classifier/models/sklearn.ipynb)
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- [TensorFlow](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/tensorflow.ipynb)
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- [Pytorch](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/pytorch.ipynb)
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- [Keras](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/keras.ipynb)
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- [XGBoost](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/xgboost.ipynb)
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- [sklearn](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/iris-classifier/models/sklearn.ipynb)
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‎examples/iris-classifier/models/keras.ipynb

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"That's it! See the [example on GitHub](https://github.com/cortexlabs/cortex/tree/0.9/examples/iris-classifier) for how to deploy the model as an API."
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‎examples/iris-classifier/models/pytorch.ipynb

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‎examples/iris-classifier/models/sklearn.ipynb

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"We also need to upload the mean and standard deviation, so that the [pre-inference request handler](https://github.com/cortexlabs/cortex/blob/0.9/examples/iris-classifier/handlers/sklearn.py) can normalize the data before making real-time predictions."
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‎examples/iris-classifier/models/tensorflow.ipynb

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‎examples/iris-classifier/models/xgboost.ipynb

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‎examples/sentiment-analysis/README.md

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You can run the code that generated the exported BERT model [here](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/sentiment-analysis/bert.ipynb).
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‎examples/sentiment-analysis/bert.ipynb

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‎examples/text-generator/README.md

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```
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<!-- CORTEX_VERSION_MINOR -->
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You can run the code that generated the exported GPT-2 model [here](https://colab.research.google.com/github/cortexlabs/cortex/blob/master/examples/text-generator/gpt-2.ipynb).
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You can run the code that generated the exported GPT-2 model [here](https://colab.research.google.com/github/cortexlabs/cortex/blob/0.9/examples/text-generator/gpt-2.ipynb).
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## Add request handling
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‎examples/text-generator/gpt-2.ipynb

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},
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"source": [
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"<!-- CORTEX_VERSION_MINOR x2 -->\n",
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"We also need to upload `vocab.bpe` and `encoder.json`, so that the [encoder](https://github.com/cortexlabs/cortex/blob/master/examples/text-generator/encoder.py) in the [pre-inference request handler](https://github.com/cortexlabs/cortex/blob/master/examples/text-generator/handler.py) can encode the input text before making a request to the model."
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"We also need to upload `vocab.bpe` and `encoder.json`, so that the [encoder](https://github.com/cortexlabs/cortex/blob/0.9/examples/text-generator/encoder.py) in the [pre-inference request handler](https://github.com/cortexlabs/cortex/blob/0.9/examples/text-generator/handler.py) can encode the input text before making a request to the model."
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]
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},
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{
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},
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"source": [
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"<!-- CORTEX_VERSION_MINOR -->\n",
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"That's it! See the [example on GitHub](https://github.com/cortexlabs/cortex/tree/master/examples/text-generator) for how to deploy the model as an API."
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"That's it! See the [example on GitHub](https://github.com/cortexlabs/cortex/tree/0.9/examples/text-generator) for how to deploy the model as an API."
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]
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}
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]

‎pkg/consts/consts.go

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@@ -17,7 +17,7 @@ limitations under the License.
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package consts
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var (
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CortexVersion = "master" // CORTEX_VERSION
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CortexVersion = "0.9.0" // CORTEX_VERSION
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ContextCacheDir = "/mnt/context"
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EmptyDirMountPath = "/mnt"

‎pkg/workloads/cortex/client/cortex/client.py

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@@ -44,7 +44,7 @@ def __init__(self, aws_access_key_id, aws_secret_access_key, operator_url):
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self.aws_access_key_id = aws_access_key_id
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self.aws_secret_access_key = aws_secret_access_key
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self.headers = {
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"CortexAPIVersion": "master", # CORTEX_VERSION
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"CortexAPIVersion": "0.9.0", # CORTEX_VERSION
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"Authorization": "CortexAWS {}|{}".format(
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self.aws_access_key_id, self.aws_secret_access_key
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),

‎pkg/workloads/cortex/client/setup.py

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setup(
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name="cortex",
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version="master", # CORTEX_VERSION
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version="0.9.0", # CORTEX_VERSION
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description="",
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author="Cortex Labs",
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author_email="[email protected]",

‎pkg/workloads/cortex/consts.py

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# See the License for the specific language governing permissions and
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# limitations under the License.
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CORTEX_VERSION = "master"
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CORTEX_VERSION = "0.9.0"

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